A survey of visualization techniques for comparing event sequences

Abstract

Event sequence data is a special type of time-dependent data that captures information about the order in which discrete events occur. The time-dimension is one of the factors that makes event sequence data hard to understand. Other factors that contribute to this complexity are the dimensionality in terms of the amount of events and attributes, the frequency of events in terms of consistency and density, varying durations, and parallel occurrences. When end-users need to compare event sequences, all these characteristics need to be considered and justified. In this state-of-the-art report we review visualization techniques for the event sequence comparison task. We focus specifically on comparison, in contrast to general event sequence visualization, and review how different aspects, such as the data attributes or granularity, affect the comparison. We define a taxonomy based on five dimensions: Scale, Comparison Type, Size, Data, and Visualization & Interaction. Based on these dimensions, we provide an overview of the literature of the past 17 years. This overview is accompanied with an analysis of the strengths and weaknesses of the proposed techniques. Furthermore, we identify current gaps and research challenges in the literature.